scholarly journals Detection of Acoustic Emission Characteristics of Plant According to Water Stress Condition

Author(s):  
Petr Dostál ◽  
Piyapong Sriwongras ◽  
Václav Trojan

Utilization of acoustic emission (AE) technique for understanding of plant reaction due to the change of environmental conditions was performed in this research. The object of present experiment is to study the acoustic emission characteristics acquired from water-stressed plant and well-watered plant. In this study, two specimens of maize were chosen to be test under controllable environment. The outcomes of this experiment revealed that a large number of AE signals detected from plant were able to be noticed, especially in counts number of AE signals, when the plant was under water stress condition, whereas this situation of AE signals did not appear on plat with well water condition. Moreover, multiple regression calculated to find the correlation between AE parameter received from maize and environmental parameters presented that air temperature was the most important parameter affecting to the RMS value as an AE parameter showing cavitation event of test plant. As these results, AE signals detected from test maize is capable of indicating its water stress condition. Therefore, using of AE method for monitoring the plant is considerably interested as state-of –art technique for increasing productivity, especially in agricultural field.

Agro-Science ◽  
2015 ◽  
Vol 12 (1) ◽  
pp. 17
Author(s):  
S Ovie ◽  
GU Nnaji ◽  
PO Oviasogie ◽  
PE Osayande ◽  
P Irhemu

2013 ◽  
Vol 31 (2) ◽  
pp. 291-302 ◽  
Author(s):  
F.B. Cerqueira ◽  
E.A.L. Erasmo ◽  
J.I.C. Silva ◽  
T.V. Nunes ◽  
G.P. Carvalho ◽  
...  

The objective of this study was to evaluate the competitiveness of two cultivars of upland rice drought-tolerant, cultured in coexistence with weed S. verticillata, under conditions of absence and presence of water stress. The experiment was conducted in a greenhouse at the Experimental Station of the Universidade Federal de Tocantins, Gurupi-TO Campus. The experimental design was completely randomized in a factorial 2 x 2 x 4 with four replications. The treatments consisted of two rice cultivars under two water conditions and four densities. At 57 days after emergence, were evaluated in rice cultivars and weed S. verticillata leaf area, dry weight of roots and shoots and total concentration and depth of roots. Was also evaluated in rice cultivars, plant height and number of tillers. Water stress caused a reduction in leaf area, the concentration of roots and vegetative components of dry matter (APDM, and MSR MST) of rice cultivars and Jatoba Catetão and weed S. verticillata. The competition established by the presence of the weed provided reduction of all vegetative components (MSPA, and MSR MST) of cultivars and Jatoba Catetão. It also decreased the number of tillers, the concentration of roots and leaf area. At the highest level of weed competition with rice cultivars, a greater decrease in vegetative components and leaf area of culture, regardless of water conditions.


2019 ◽  
Vol 11 (14) ◽  
pp. 1684 ◽  
Author(s):  
Chao Zhang ◽  
Jiangui Liu ◽  
Taifeng Dong ◽  
Elizabeth Pattey ◽  
Jiali Shang ◽  
...  

Accurate information of crop growth conditions and water status can improve irrigation management. The objective of this study was to evaluate the performance of SAFYE (simple algorithm for yield and evapotranspiration estimation) crop model for simulating winter wheat growth and estimating water demand by assimilating leaf are index (LAI) derived from canopy reflectance measurements. A refined water stress function was used to account for high crop water stress. An experiment with nine irrigation scenarios corresponding to different levels of water supply was conducted over two consecutive winter wheat growing seasons (2013–2014 and 2014–2015). The calibration of four model parameters was based on the global optimization algorithms SCE-UA. Results showed that the estimated and retrieved LAI were in good agreement in most cases, with a minimum and maximum RMSE of 0.173 and 0.736, respectively. Good performance for accumulated biomass estimation was achieved under a moderate water stress condition while an underestimation occurred under a severe water stress condition. Grain yields were also well estimated for both years (R2 = 0.83; RMSE = 0.48 t∙ha−1; MRE = 8.4%). The dynamics of simulated soil moisture in the top 20 cm layer was consistent with field observations for all scenarios; whereas, a general underestimation was observed for total water storage in the 1 m layer, leading to an overestimation of the actual evapotranspiration. This research provides a scheme for estimating crop growth properties, grain yield and actual evapotranspiration by coupling crop model with remote sensing data.


2015 ◽  
Vol 20 (4) ◽  
pp. 297-303 ◽  
Author(s):  
Abdullah Al Mahmud ◽  
Mohammad Hossain ◽  
Mohinder Singh Kadian ◽  
Md. Azizul Hoque

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